Triple
T9622395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goyang |
E232375
|
entity |
| Predicate | hasAdministrativeDistrict |
P15909
|
FINISHED |
| Object |
Ilsandong-gu
Ilsandong-gu is a district of the city of Goyang in Gyeonggi Province, South Korea, known as a residential and commercial hub within the Seoul Capital Area.
|
E851256
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ilsandong-gu | Statement: [Goyang, hasAdministrativeDistrict, Ilsandong-gu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ilsandong-gu Context triple: [Goyang, hasAdministrativeDistrict, Ilsandong-gu]
-
A.
Geumjeong-gu
Geumjeong-gu is a district in Busan, South Korea, known for its residential areas, transportation hubs, and proximity to Geumjeongsan Mountain.
-
B.
Kangseo-gu
Kangseo-gu is the romanized name of Gangseo District, an administrative district of Seoul, South Korea.
-
C.
Jinhae-gu
Jinhae-gu is a coastal district in Changwon, South Korea, best known for its large naval base and famous annual cherry blossom festival.
-
D.
Gyeyang-gu
Gyeyang-gu is an administrative district of Incheon, South Korea, known for its mix of residential areas, historical sites, and access to natural attractions like Gyeyang Mountain.
-
E.
Dong-gu
Dong-gu is an administrative district of the metropolitan city of Ulsan in South Korea, known for its coastal location and industrial facilities.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ilsandong-gu Triple: [Goyang, hasAdministrativeDistrict, Ilsandong-gu]
Generated description
Ilsandong-gu is a district of the city of Goyang in Gyeonggi Province, South Korea, known as a residential and commercial hub within the Seoul Capital Area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ilsandong-gu Target entity description: Ilsandong-gu is a district of the city of Goyang in Gyeonggi Province, South Korea, known as a residential and commercial hub within the Seoul Capital Area.
-
A.
Geumjeong-gu
Geumjeong-gu is a district in Busan, South Korea, known for its residential areas, transportation hubs, and proximity to Geumjeongsan Mountain.
-
B.
Kangseo-gu
Kangseo-gu is the romanized name of Gangseo District, an administrative district of Seoul, South Korea.
-
C.
Jinhae-gu
Jinhae-gu is a coastal district in Changwon, South Korea, best known for its large naval base and famous annual cherry blossom festival.
-
D.
Gyeyang-gu
Gyeyang-gu is an administrative district of Incheon, South Korea, known for its mix of residential areas, historical sites, and access to natural attractions like Gyeyang Mountain.
-
E.
Dong-gu
Dong-gu is a district-level administrative area within the metropolitan city of Daejeon in South Korea.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca848793ec8190a93a12383a754dc0 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9ad505588190b8c81ce09f1904ec |
completed | April 1, 2026, 10:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f69ad0448190a2f472555384f0be |
completed | April 9, 2026, 12:45 a.m. |
| NEDg | Description generation | batch_69d6fa2bb2ec8190aa099988a6c225eb |
completed | April 9, 2026, 1 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6fd10dbc08190a297073e1b737566 |
completed | April 9, 2026, 1:12 a.m. |
Created at: March 30, 2026, 8:10 p.m.